What are the hardware requirements for GLM 5.1 AWQ?

GLM 5.1 AWQ requires approximately 119.9 GB of VRAM and supports a context window of 198K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GLM 5.1 AWQ and how large is it?

GLM 5.1 AWQ is developed by QuantTrio, a model with 753.9b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate GLM 5.1 AWQ?

GLM 5.1 AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 5.1 AWQ by QuantTrio — VRAM 119.9GB, 198K context

Name: GLM 5.1 AWQ
Author: QuantTrio

GLM 5.1 AWQ is an open-source language model by QuantTrio. Features: 753.9b LLM, VRAM: 119.9GB, Context: 198K, License: mit, MoE, Quantized, LLM Explorer Score: 0.31.

Arxiv:2602.15763 4-bit Awq Conversational Endpoints compatible Glm moe dsa Moe Quantized Region:us Safetensors Sharded Tensorflow Vllm

Model Card on HF 🤗: https://huggingface.co/QuantTrio/GLM-5.1-AWQ

GLM 5.1 AWQ Benchmarks

LLME Score: 0.31209

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

🌟 Advertise your project 🚀

GLM 5.1 AWQ Parameters and Internals

LLM Name	GLM 5.1 AWQ
Repository 🤗	https://huggingface.co/QuantTrio/GLM-5.1-AWQ
Base Model(s)	ZhipuAI/GLM-5.1 ZhipuAI/GLM-5.1
Model Size	753.9b
Required VRAM	119.9 GB
Updated	2026-05-08
Maintainer	QuantTrio
Model Type	glm_moe_dsa
Model Files	3.0 GB: 1-of-141 3.0 GB: 2-of-141 3.0 GB: 3-of-141 3.0 GB: 4-of-141 3.0 GB: 5-of-141 3.0 GB: 6-of-141 3.0 GB: 7-of-141 2.9 GB: 8-of-141 3.0 GB: 9-of-141 3.0 GB: 10-of-141 3.0 GB: 11-of-141 3.0 GB: 12-of-141 3.0 GB: 13-of-141 3.0 GB: 14-of-141 3.0 GB: 15-of-141 3.0 GB: 16-of-141 3.0 GB: 17-of-141 3.0 GB: 18-of-141 3.0 GB: 19-of-141 3.0 GB: 20-of-141 3.0 GB: 21-of-141 3.0 GB: 22-of-141 3.0 GB: 23-of-141 3.0 GB: 24-of-141 3.0 GB: 25-of-141 3.0 GB: 26-of-141 3.0 GB: 27-of-141 3.0 GB: 28-of-141 3.0 GB: 29-of-141 3.0 GB: 30-of-141 3.0 GB: 31-of-141 3.0 GB: 32-of-141 3.0 GB: 33-of-141 3.0 GB: 34-of-141 3.0 GB: 35-of-141 3.0 GB: 36-of-141 3.0 GB: 37-of-141 3.0 GB: 38-of-141 3.0 GB: 39-of-141 3.0 GB: 40-of-141
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	GlmMoeDsaForCausalLM
License	mit
Context Length	202752
Model Max Length	202752
Transformers Version	5.4.0
Vocabulary Size	154880

Best Alternatives to GLM 5.1 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
GLM 5	198K / 237.3 GB	484419	2079
GLM 5.1	198K / 237.3 GB	23998	1001
GLM 5.1 FP8	198K / 237.6 GB	934979	102
GLM 5.1 FP8	198K / 243 GB	860	5

Note: green Score (e.g. "73.2") means that the model is better than QuantTrio/GLM-5.1-AWQ.

Rank the GLM 5.1 AWQ Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

What open-source LLMs or SLMs are you in search of? 53651 in total.

Email us: info@extractum.io. Our Privacy Policy | Terms and Conditions | Suggest an improvement.

Our Social Media →

Original data from HuggingFace, OpenCompass and various public git repos.

Check out Ag3ntum — our secure, self-hosted AI agent for server management.

Release v20260328a

Support LLM Explorer

GLM 5.1 AWQ by QuantTrio

» All LLMs » QuantTrio » GLM 5.1 AWQ URL Share it on

GLM 5.1 AWQ Benchmarks

GLM 5.1 AWQ Parameters and Internals

Best Alternatives to GLM 5.1 AWQ

Rank the GLM 5.1 AWQ Capabilities

What open-source LLMs or SLMs are you in search of? 53651 in total.